THE UNIVERSITY OF CALGARY Algorithms for Automatic Vectorization of Scanned Maps
Bibliographic record
Abstract
The proliferation of Geographic Information System (GIS) in industry and research has lead to the need for converting the available analog geospatial data to digital form. Although maps can be scanned, they cannot be used directly in a GIS system without processing. All the available commercial raster to vector conversion software are semi-automatic and require an operator for digitization and verification. Thus automatic algorithms are required for faster and reliable conversion of maps where the operator is required only for verification. Methods for automatic vectorization of scanned maps deal with polygons, lines and points. The focus of this research is on the extraction of linear features from scanned maps and satellite imageries using skeletonization. Two methods that are examined are skeletonization by Voronoi Diagram and Mathematical Morphology. Connectivity is established between disconnected lines using Least Square Parabola (LSP). The objectives of this research are to compare the two vectorization methods and examine the application of LSP for gap filling.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".